Pattern Based Information Extraction System in Business News Articles

Business news journals provide a rich resource of business events, which enable domain experts to further understand the spatio-temporal changes occur among a set of firms and people. However, extracting structured data from journal resource that is text-based and unstructured is a non-trivial challenge. This project designs and implements a Business Information Extraction System, which combines advanced natural language processing (NLP) tools and knowledge-based extraction patterns to process and extract information of target business event from news journals automatically. The performance evaluation on the proposed system suggests that IE techniques works well on business event extraction and it is promising to apply the technique to extract more types of business events.Master of Science in Information Scienc